Gender: Male 
Age: 25-34
Nationality: United Kingdom
Ethnicity: Black or African American 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 7
Home: Rent 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to classical music;Listen to hiphop and rap;Exercise;Use social media;Go to museums and galleries;Attend football matches;Watch sports;Other (Please specify) Read Books
Devices used daily: Smartphone;Laptop;Tablet;Smartwatch 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Google Gemini;Microsoft Bing AI;Snapchat My AI;Meta Llama 2;Pi 
LLM use cases: Coding;Brainstorming;Translation;Writing (e.g., composing emails);Proofreading/Editing (e.g., grammar, spelling, structure improvements);Generic chatbot conversation;Solving math or logical problems;Analyze data;Generate art;Play games;Completing assignments;Learning (e.g., explaining complex concepts in simple terms);Get information about current events;Summarizing long texts;Answering questions about general knowledge;Paraphrasing or finding synonyms;Collecting references 
Contexts of LLM use: Personal;Technical;Learning;Work 
Prompt 1: Nazi History Summary
Prompt 2: Top 10 UK Insurance Company
Prompt 3: Acute renal failure vague symptoms
Prompt 4: What day is Mohammed Ali's birthday ?
Prompt 5: Hematemesis Classification
Prompt 6: Boerhaave syndrome Diagnosis
Prompt 7: Google Pixel 9 pricing 
Prompt 8: Bubble wrap ideas 
Prompt 9: Kitchen Cabinet Pricing Guide
Prompt 10: Endometriosis Overview and Treatment plan